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Review Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Concentrations in Response to Diets: A Narrative Review of Recent Evidence

Mohammad M. H. Abdullah 1 , Itzel Vazquez-Vidal 2, David J. Baer 3, James D. House 4 , Peter J. H. Jones 5 and Charles Desmarchelier 6,*

1 Department of Food Science and Nutrition, Kuwait University, Kuwait City 10002, Kuwait; [email protected] 2 Richardson Centre for Functional Foods & Nutraceuticals, University of Manitoba, Winnipeg, MB R3T 6C5, Canada; [email protected] 3 United States Department of Agriculture, Agricultural Research Service, Beltsville, MD 20705, USA; [email protected] 4 Department of Food and Human Nutritional Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada; [email protected] 5 Nutritional Fundamentals for Health, Vaudreuil-Dorion, QC J7V 5V5, Canada; [email protected] 6 Aix Marseille University, INRAE, INSERM, C2VN, 13005 Marseille, France * Correspondence: [email protected]   Abstract: The number of nutrigenetic studies dedicated to the identification of single nucleotide Citation: Abdullah, M.M.H.; polymorphisms (SNPs) modulating blood profiles in response to dietary interventions has Vazquez-Vidal, I.; Baer, D.J.; House, increased considerably over the last decade. However, the robustness of the evidence-based sci- J.D.; Jones, P.J.H.; Desmarchelier, C. ence supporting the area remains to be evaluated. The objective of this review was to present Common Genetic Variations Involved recent findings concerning the effects of interactions between SNPs in involved in cholesterol in the Inter-Individual Variability of and transport, and dietary intakes or interventions on circulating cholesterol concen- Circulating Cholesterol trations, which are causally involved in cardiovascular diseases and established biomarkers of Concentrations in Response to Diets: cardiovascular health. We identified recent studies (2014–2020) that reported significant SNP–diet A Narrative Review of Recent NPC1L1, ABCA1, ABCG5, ABCG8, APOA1, APOA2, Evidence. Nutrients 2021, 13, 695. interactions in 14 cholesterol-related genes ( https://doi.org/10.3390/nu13020695 APOA5, APOB, APOE, CETP, CYP7A1, DHCR7, LPL, and LIPC), and which replicated associations observed in previous studies. Some studies have also shown that combinations of SNPs could explain Academic Editor: a higher proportion of variability in response to dietary interventions. Although some findings still David Cameron-Smith need replication, including in larger and more diverse study populations, there is good evidence that some SNPs are consistently associated with differing circulating cholesterol concentrations in Received: 31 December 2020 response to dietary interventions. These results could help clinicians provide patients with more Accepted: 12 February 2021 personalized dietary recommendations, in order to lower their risk for . Published: 22 February 2021 Keywords: ; -diet interaction; personalized nutrition; single nucleotide polymorphism; Publisher’s Note: MDPI stays neutral genetic variant; cardiovascular diseases; nutrigenetics with regard to jurisdictional claims in published maps and institutional affil- iations. 1. Introduction Personalized nutrition is the next frontier for the food and health industries. Presently, consumers report high expectations for the role proper genetic information could play in Copyright: © 2021 by the authors. their dietary choices for the prevention and treatment of chronic diseases [1,2]. Cardiovas- Licensee MDPI, Basel, Switzerland. cular disease (CVD) is still the leading cause of death globally, and it is estimated that 90% This article is an open access article of cases are preventable, with healthy diet considered as the first line of intervention [3,4]. distributed under the terms and conditions of the Creative Commons Lowering of blood lipid concentrations is a major target in both the primary and secondary Attribution (CC BY) license (https:// prevention of CVD, but high interindividual variability exists in response to any given creativecommons.org/licenses/by/ dietary intervention [5]. 4.0/).

Nutrients 2021, 13, 695. https://doi.org/10.3390/nu13020695 https://www.mdpi.com/journal/nutrients Nutrients 2021, 13, 695 2 of 15

Genome-wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with the variability of fasting blood cholesterol concentrations. These genetic variations have been estimated to explain about 30% of total variance [6,7]. Yet, the application of the results to personalized dietary recommendations is not straightforward because these studies usually do not consider the effect of diet. Several clinical trials have investigated the relationship between dietary interventions and blood lipid concentrations, considering the genetic characteristics of the participants. However, by design, they usually only focus on individual SNPs, resulting in a relatively low ex- plained genetic variance [8,9]. A greater part of the variability in blood lipid concentrations could be explained by the additive effects of several SNPs, which, taken individually, may only have small, and barely significant, effects [10,11]. While numerous studies have reported SNPs that are significantly associated with blood cholesterol concentrations in response to various diets [8], there is a need to review additional data generated in this field. The objective of this narrative review is, thus, to summarize recent findings of inter- actions between individual SNPs in major cholesterol-related genes and dietary intakes, relative to shaping circulating cholesterol concentrations. The review also highlights stud- ies that used combinations of SNPs to increase the explained variability in cholesterol concentrations following dietary interventions. Looking at the sum of evidence accumu- lated in the field enables discussion of what is still missing in order to put this knowledge into practice.

2. Search Process and Criteria For the purpose of this review, we considered only genes that are explicitly involved in cholesterol absorption, metabolism, and transport pathways (Figure1). A systematic search was utilized, and gene–diet interaction studies relative to the genes of interest were retrieved, with no restriction on study design, dietary protocol, population, or qual- ity throughout the preliminary search. Searches were performed on articles published between 1 January 2014 (as a follow-up to our previous review on the topic [8]) and 30 September 2020 using the MEDLINE (PubMed) database, and searching string varia- tions of the following keywords: (diet OR gene-diet OR dietary) AND (cholesterol) AND (SNP OR polymorphism OR genetic variant). A total of 291 articles were identified and examined individually to exclude research articles that did not report statistically signif- icant cholesterol responses to gene–diet interactions, did not present clear associations, or did not provide data details. With the exclusion of all review articles, animal studies, and articles in languages other than English, as well as those considering factors other than diet, such as physical activity, alcohol intake, smoking, and others, a total of 21 distinct research articles were eligible for inclusion in the individual SNP–diet interaction analysis (Section3), and four articles were eligible for the combinatory patterns of SNPs analysis (Section4) below. The following sections present statistically significant findings regarding the effects of interactions between SNPs (taken individually or in combinatory patterns) and dietary intakes on circulating cholesterol concentrations in observational studies and dietary interventions. Nomenclature for all genes in this work is reported according to international standards of the Organization (HUGO) [12], with description of variants at the DNA level and reference to SNPs as rs#-xx homozygotes or rs#-x , even when authors of some of the reviewed articles reported variants as defined by their encoding changes, using the 3-letter code or the 1-letter code, with no mention of the rs# for their SNPs. Where applicable in the sections below, the meanings of such amino acid codes are addressed. Nutrients 2021, 13, x FOR PEER REVIEW 3 of 17

articles were identified and examined individually to exclude research arti- cles that did not report statistically significant cholesterol responses to gene– diet interactions, did not present clear associations, or did not provide data details. With the exclusion of all review articles, animal studies, and articles in languages other than English, as well as those considering factors other than diet, such as physical activity, alcohol intake, smoking, and others, a to- tal of 21 distinct research articles were eligible for inclusion in the individual Nutrients 2021, 13, 695 SNP–diet interaction analysis (Section 3), and four articles were eligible for 3 of 15 the combinatory patterns of SNPs analysis (Section 4) below.

FigureFigure 1. Summary 1. Summary of genes of of genes lipid of metabolism lipid metabo andlism transport and transport pathways pathways involved involv in the variabilityed in the variability of circulating of cir- cholesterol concentrationsculating cholesterol in response concentrations to diets. Genes in displayedresponse to are diets. those Genes for which displayed significant are those SNP–diet for which interactions significant have been reportedSNP–diet recently interactions (2014–2020). haveABCA1 been, ATP reported binding recently cassette subfamily(2014–2020). A member ABCA1 1;, ABCG5/8ATP binding, ATP cassette binding subfamily cassette subfamily A G membermember 5/8; APOA1, 1; ABCG5/8apolipoprotein, ATP binding A1; APOA2 cassette, subfamilyapolipoprotein G member A2; APOA5 5/8; APOA1,, apolipoprotein A5; APOB A1; APOA2, apolipoprotein, apolipo- B; APOE, A2; APOA5, apolipoprotein A5; APOB, ; APOE, ; CE, cholesteryl esters; apolipoprotein E; CE, cholesteryl esters; CETP, cholesteryl ester transfer protein; CYP7A1, cholesterol 7-alpha-hydroxylase; DHCR7, CETP, cholesteryl ester transfer protein; CYP7A1, cholesterol 7-alpha-hydroxylase; DHCR7, 7-dehydrocholesterol re- 7-dehydrocholesterol reductase; HDL, high-density ; IDL, intermediate-density lipoprotein; LDL, low-density ductase; HDL, high-density lipoprotein; IDL, intermediate-density lipoprotein; LDL, low-density lipopro- lipoprotein;tein; LPL,, lipoprotein lipaselipase;;LIPC LIPC, ,hepatic lipase; NPC1L1; NPC1L1, NPC1, NPC1 like like intracellular intracellular cholesterol cholesterol transporter transporter 1; TG, 1; ;TG, VLDL,triglycerides; very-low-density VLDL, lipoprotein very-low-density lipoprotein

3. StudiesThe Investigating following thesections Effect present of SNPs statis Takentically Individually significant findings regard- Ining this the section, effects of a summaryinteractions of between the recent SNPs evidence (taken onindividually statistically or significantin combi- gene– diet interactionsnatory patterns) is presented and dietary considering intakes on individual circulating SNP cholesterol data (Table concentrations1). This approach has been the most widely utilized in research and reported in the literature due to both technical and statistical reasons. For instance, sequencing and genotyping techniques, such as commercially available SNP assays and PCR methods, are presently low-cost and easy-to-implement. Moreover, dietary interventions are typically expensive to carry out, and usually have relatively low sample sizes, resulting in limited statistical power. Nonetheless, they allow for identification of new genetic associations based on known or predicted SNP functions. Importantly, the SNP–diet interactions identified in clinical settings also constitute good candidates for building genetic risk scores (GRS) of cumula- tive SNPs, aiming at predicting practical changes in biomarkers of health in response to dietary intakes. Nutrients 2021, 13, 695 4 of 15

Table 1. Summary of epidemiological and dietary intervention studies reporting significant effects of individual SNP–diet interactions on circulating cholesterol concentrations.

Population and Author Gene SNP Study Design Diet Major Cholesterol Outcomes Ethnicity HDL-C concentrations negatively correlated Jacobo-Albavera et al. 1598 premenopausal with CHO intake and positively correlated with ABCA1 rs9282541 Cross-sectional Dietary CHO and intakes (2015) [13] females, Mexicans fat intake in T carriers but not CC homozygotes Lower LDL-C/HDL-C concentration ratios in A 7-d of washout diet followed 56 healthy adults, Liu et al. (2014) [14] ABCA1 rs2230806 Dietary intervention allele male carriers and GG female homozygotes by 6-d of high-CHO/low-fat diet Chinese after vs. before high-CHO/low-fat diet Higher TC and LDL-C concentrations in GG Abdullah et al. 101 healthy adults, ABCG5 rs6720173 Crossover Dairy vs. dairy-free diets homozygotes vs. C allele carriers after 3 (2016) [15] Canadians servings/d of dairy vs. dairy-free diets 750 µg β-cryptoxanthin and Lower TC concentrations in CC homozygotes vs. Granado-Lorencio et al. 19 postmenopausal ABCG8 rs6544718 Crossover 1.5 g/d PS, T allele carriers after β-cryptoxanthin + PS (2014) [16] females, Spanish single and combined combined intake Lower HDL-C concentrations in GG de Luis et al. (2018) [17] APOA1 rs670 Dietary intervention Hypocaloric diet of one arm 82 obese adults, Spanish homozygotes vs. A allele carriers at baseline and after hypocaloric diet Higher HDL-C concentrations in A allele carriers Hypocaloric high-fat vs. 282 obese adults, de Luis et al. (2019) [18] APOA1 rs670 Dietary intervention vs. GG homozygotes at baseline and after both low-fat diets Spanish high-fat and low-fat diets Higher LDL-C/HDL-C concentration ratio in CC Noorshahi et al. Dietary SFA intake 697 type 2 diabetic APOA2 rs5082 Cross-sectional homozygotes vs. T allele carriers with higher (2016) [19] (>28.5 g/d), assessed by FFQ adults, Iranians SFA intake 200 young Dominguez-Reyes et al. Dietary fat intake, assessed Lower HDL-C concentrations and higher PUFA APOA5 rs662799 Cross-sectional normal-weight and (2015) [20] by FFQ intake in C allele carriers vs. TT homozygotes obese adults, Mexicans Lower HDL-C concentrations in CC Dietary intake, assessed by 1128 premenopausal Lim et al. (2014) [21] APOA5 rs662799 Cross-sectional homozygotes with higher total energy intake 24-h recall and FFQ females, Koreans (≥2001 kcal/d) Total energy and Higher TC and LDL-C concentrations in G allele Cross-sectional Doo et al. (2015) [22] APOB rs1469513 macronutrient intake, assessed 6470 adults, Koreans carriers with higher energy or fat intake, and in (‘KoGES’ Study) by FFQ AA homozygotes with higher CHO intake Nutrients 2021, 13, 695 5 of 15

Table 1. Cont.

Population and Author Gene SNP Study Design Diet Major Cholesterol Outcomes Ethnicity 16-wk parallel dietary 120 adults with Lower TC concentrations only in TT Isoenergetic diets rich in SFA, Shatwan et al. (2017) [23] APOE rs1064725 intervention moderate cardiovascular homozygotes after MUFA-rich diet vs. SFA-rich MUFA, or n-6 PUFA (‘DIVAS’ Study) risk, Caucasians or n-6 PUFA-rich diets Lower LDL-C concentrations in APOE ε2 carriers rs429258 Cross-sectional Dietary fat intake, assessed Weber et al. (2016) [24] APOE 348 diabetics, Germans with lower vs. higher intake frequencies of butter, rs7412 (German Diabetes Study) by FFQ cream cake, French fries, or alcoholic beverages 63 mildly rs429258 Greater reduction in LDL-C concentrations after Mackay et al. (2015) [25] APOE Crossover 2 g/d of PS hypercholesterolemic rs7412 PS intake in APOE ε4 vs. APOE ε3 carriers adults, Canadians Greater decreases in TC concentrations in carriers 24-wk five-arm parallel Replacing SFA with either 389 adults at increased of E4 vs. E3/E3 when SFA was replaced with low rs429258 Griffin et al. (2018) [26] APOE dietary intervention MUFA or carbohydrate of risk of developing MetS, GI carbohydrate on a lower fat diet, and an rs7412 (‘RISCK’ Study) high or low GI white Caucasians increase in TC concentrations when SFA was replaced with MUFA and high GI carbohydrates Mediterranean diet (35% fat, Higher HDL-C concentrations after Garcia-Rios et al. 1-y dietary intervention 424 MetS subjects, CETP rs3764261 22% MUFA) vs. low-fat diet Mediterranean diet in T allele carriers vs. (2016) [27] (‘CORDIOPREV’ Study) Spanish (28% fat, 12% MUFA) GG homozygotes Population-based Lower TC concentrations and higher fish intakes Hosseini-Esfahani et al prospective design Usual dietary intake, assessed CETP rs3764261 4700 adults, Iranians in T allele carriers vs. GG homozygotes after (2019) [28] (Tehran Lipid and by FFQ 3.6 years of follow-up Study) Higher TC concentrations in G allele carriers vs. Abdullah et al. 101 healthy adults, CYP7A1 rs3808607 Crossover Dairy vs. dairy-free diets TT homozygotes after 3 servings/d of dairy vs. (2016) [15] Canadians dairy-free diets 63 mildly Greater reduction in LDL-C concentrations after Mackay et al. (2015) [25] CYP7A1 rs3808607 Crossover 2 g/d of PS hypercholesterolemic PS intake in GG vs. TT homozygotes adults, Canadians 30 mildly Lower TC concentrations after 3 g/d of high Barley β-glucan vs. Wang et al. (2016) [29] CYP7A1 rs3808607 Crossover hypercholesterolemic molecular weight barley β-glucan in G allele control diet adults, Canadians carriers vs. TT homozygotes Nutrients 2021, 13, 695 6 of 15

Table 1. Cont.

Population and Author Gene SNP Study Design Diet Major Cholesterol Outcomes Ethnicity Higher LDL-C concentrations in A allele carriers Abdullah et al. 101 healthy adults, DHCR7 rs760241 Crossover Dairy vs. dairy-free diets vs. GG homozygotes after 3 servings/d of dairy (2016) [15] Canadians vs. dairy-free diets 7-d of washout diet followed by 6-d of high-CHO 56 healthy Chinese Higher HDL-C concentrations in G allele male Zhu et al. (2014) [30] LPL rs326 Dietary intervention (70% energy)/low-fat Han youth carriers after vs. before high-CHO/low-fat diet (~14% energy) diet Cross-sectional 788 type 2 diabetes cases Ayyappa et al. Dietary intakes, assessed Higher HDL-C concentrations in T allele carriers LPL rs1121923 (Chennai Urban Rural and 1057 controls, (2017) [31] by FFQ with high fat diet vs. CC homozygotes Epidemiological Study) Asian Indians Higher HDL-C concentrations in CC Comparing a high-fat Western 42 adults, Caribbean homozygotes after high-fat Western diet Smith et al. (2017) [32] LIPC rs1800588 Crossover diet and a low-fat traditional Hispanic descent (39% energy) vs. low-fat traditional Hispanic diet Hispanic diet (20% energy) 2-y randomized 743 overweight or Higher TC concentrations after high fat intake, weight-loss Xu et al. (2015) [33] LIPC rs2070895 Dietary intakes obese adults, and higher HDL-C concentrations after low fat dietary intervention multiethnic groups intake, in A allele carriers vs. GG homozygotes (‘POUNDS LOST’ Study) 750 µg β-cryptoxanthin Granado-Lorencio et al. 19 postmenopausal Higher TC concentrations in CC homozygotes vs. NPC1L1 rs2072183 Crossover and 1.5 g/d PS, (2014) [16] females, Spanish G allele carriers after PS intake only single and combined Abbreviations: ABC, ATP-binding cassette subfamily; APO, ; CETP, cholesteryl ester transfer protein; CHO, carbohydrate; DHCR7, 7-dehydrocholesterol reductase; CYP7A1, cholesterol 7-alpha-hydroxylase; FFQ, food frequency questionnaire; GI, glycemic index; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LPL, ; LIPC, hepatic lipase; MetS, ; MUFA, monounsaturated fatty acids; SFA, saturated fatty acids; SNP, single nucleotide polymorphism; PUFA, polyunsaturated fatty acids; NPC1L1, NPC1 like intracellular cholesterol transporter 1; PS, plant sterols, TC, total cholesterol. Nutrients 2021, 13, 695 7 of 15

3.1. SNPs in Genes Encoding Transporters Involved in Cholesterol Absorption NPC1 like intracellular cholesterol transporter 1 (NPC1L1) is an apical multi-pass that mediates the transport of sterols into enterocytes and hepatocytes through clathrin-mediated endocytosis, and is essential for cholesterol trafficking [34–36]. It is now well-established that dietary plant sterols (PS) can inhibit intestinal cholesterol absorption through several mechanisms, such as competition for incorporation into mixed micelles, hydrolysis of esters by digestive , enterocyte uptake by NPC1L1, and in- corporation into [34,37]. In a randomized crossover supplementation study involving 19 post-menopausal females, participants carrying the CC genotype at rs2072183 (a synonymous variant with leucine at 272, published as L272L) in NPC1L1 showed sig- nificantly different changes in serum TC and LDL-C concentrations (0.38 ± 0.29 and 0.33 ± 0.29 mmol/L, respectively) compared to carriers of the G allele (−0.29 ± 0.10 and −0.18 ± 0.12 mmol/L, respectively) after consuming for four weeks a beverage providing 1.5 g PS/d [16]. Of note, these differences were no longer significant when an outlier in the participants homozygous for the minor allele was excluded from the statistical analysis. ATP-binding cassette subfamily A1 (ABCA1) is a basolateral membrane protein that transports cholesterol and out of enterocytes and hepatocytes, which are then collected by (encoded by APOA1) to form nascent HDL parti- cles [38,39]. A 2015 cross-sectional study involving 1598 premenopausal Mexican females found that serum HDL-C concentrations were negatively correlated with carbohydrate intake (r = −0.362), and positively correlated with fat intake (r = 0.357), in carriers of the T allele at rs9282541 in ABCA1 (published as RC/CC in the R230C missense variant, as de- fined by the amino acid change) but not in those carrying the CC genotype (published as RR in R230C variant) [13]. This variant is restricted to the Americas, where its presence explains up to 4% of the variation in HDL-C concentrations [40]. In an intervention study, 56 healthy Chinese adults received a washout diet where carbohydrate contributed 54% of energy for 7 d, followed by a high-carbohydrate/low-fat diet where carbohydrate and fat contributed 70% and 14% of energy, respectively, for 6 d [14]. Males carrying the A (published as K) allele and females carrying the GG (published as RR) genotype at rs2230806 in ABCA1 (G1051A; published as R219K, a missense variant, as defined by the amino acid change) displayed lower LDL-C/HDL-C concentration ratios (1.08 ± 0.27 vs. 1.48 ± 0.64 in males, and 1.01 ± 0.18 vs. 1.37 ± 0.33 in females) after the high-carbohydrate/low-fat diet [14]. The ATP-binding cassette subfamily G member 5 and 8 (ABCG5/G8) genes encode two transporters (ABCG5 and ABCG8) that are responsible for the excretion of sterols by hepatocytes and enterocytes [41]. Rare and common genetic variations in ABCG5/G8 have been linked to increased intestinal absorption of cholesterol and PS [42–44]. In a 2016 randomized crossover study by our group, involving 101 normocholesterolemic adults, the ABCG5 rs6720173-GG homozygotes had higher serum TC (change: 0.18 ± 0.06 vs. −0.07 ± 0.07 mmol/L) and LDL-C (change: 0.17 ± 0.05 vs. −0.06 ± 0.07 mmol/L) concen- trations relative to rs6720173-C allele carriers after three servings/d of dairy (low-fat milk, low-fat yogurt, and regular cheddar cheese) versus a dairy-free diets for 4 wk each [15]. These data replicate, to some extent, previous associations described among Spanish chil- dren [45], where male carriers of the ABCG5 rs6720173-G allele had higher plasma TC and LDL-C concentrations with a daily intake of 14.3–34.1 g saturated fatty acids (SFA) com- pared to CC homozygotes [45]. Another crossover multiple-dose supplementation study with beta-cryptoxanthin and PS in healthy postmenopausal females showed that carriers of the CC genotype of ABCG8 rs6544718 (published as A632V, a missense variant, as defined by the amino acid change) had lower serum TC concentrations (−0.34 ± 0.09 mmol/L) compared to carriers of the T allele (0.08 ± 0.20 mmol/L) after consuming a beverage providing 1.5 g/d of PS plus 750 µg beta-cryptoxanthin over 4 wk [16].

3.2. SNPs in Genes Encoding Apolipoproteins Apolipoprotein A1 (APOA1) encodes a protein that drives maturation of HDL parti- cles [46,47]. A weight loss intervention of one arm involving 82 obese patients showed that Nutrients 2021, 13, 695 8 of 15

carriers of the GG genotype at rs670 in APOA1 had lower serum HDL-C concentrations compared to A allele carriers, both at baseline (1.43 ± 0.25 vs. 1.50 ± 0.24 mmol/L) and after 12 wk (1.37 ± 0.21 vs. 1.45 ± 0.23 mmol/L) on a hypocaloric diet (reduction of 500 kcal/d) [17]. A similar 12 wk hypocaloric intervention involving 282 obese participants, by the same group, reported improvements in HDL-C concentrations among the rs670-A allele carriers versus GG homozygotes at baseline, as well as after both high-fat (1.42 ± 0.23 vs. 1.27 ± 0.18 mmol/L) and low-fat (1.53 ± 0.21 vs. 1.40 ± 0.23 mmol/L) diets [18]. (APOA2) encodes the second most common protein found in HDL particles [48]. A 2016 cross-sectional study involving 697 diabetic participants from Tehran, Iran, reported that carriers of the APOA2 rs5082-CC genotype who, based on a semi- quantitative food frequency questionnaire (FFQ) analysis, had higher SFA intake (>28.5 g/d, considering mean SFA intake of the study population as cutoff point) and displayed a higher LDL-C/HDL-C concentration ratio (2.27 ± 0.72 vs. 2.04 ± 0.63) compared to carriers of the T allele [19]. Apolipoprotein A5 (APOA5) encodes an essential protein component of several lipopro- teins such as VLDL, HDL, and chylomicrons [49]. A number of meta-analyses have demonstrated that SNPs in APOA5 may be associated with increased risk for CVD, where, in particular, carriers of the APOA5 rs662799-C allele exhibit higher concentrations of TC and TG, and lower concentrations of HDL-C compared to non-carriers [50,51]. In a cross-sectional study conducted among young Mexicans (18–25 y), participants carrying the rs662799-C allele and who traditionally consumed a diet higher in PUFAs, with median (percentile 25–75) of 10 (8–12) g/d vs. 8 (6–12) g/d also showed lower serum HDL-C con- centrations compared to TT homozygotes (1.1 (0.9–1.2) mmol/L vs. 1.2 (1.0–1.4) mmol/L); although this was not reported by the authors as part of their gene–diet interaction data [20]. In another cross-sectional study involving 1128 premenopausal Korean females, among par- ticipants who had total energy intakes ≥2001 kcal/d, based on a 24-h recall method and a semi-quantitative FFQ data analysis, rs662799-CC homozygotes displayed lower serum HDL-C concentrations (~1.16 vs. 1.42 mmol/L) compared to T allele carriers [21]. Apolipoprotein B (APOB) encodes a protein that modulates the formation and blood clearance of LDL particles and (TG)-rich . Circulating apoB-48 and apoB-100 concentrations are well-known biomarkers of cardiovascular health [52]. A cross-sectional study including 6470 Korean adults showed that among those who reported consuming higher levels of energy (≥1983.7 kcal/d), based on a semi-quantitative FFQ analysis, carriers of the minor allele (G) at rs1469513 in APOB had higher plasma TC (+2.42%) and LDL-C (+1.96%) concentrations compared to the AA homozygotes; similar TC response was seen with higher fat intake (≥19.9% energy), where the difference between G allele carriers and AA homozygotes was 2.04% [22]. In contrast, homozygotes for the A allele who consumed carbohydrates in excess of 64.9% of energy exhibited higher TC (+1.81%) and LDL-C (+2.80%) concentrations compared to G allele carriers [22]. Apolipoprotein E is one of the major involved in the transport of cholesterol and TG within the circulation [53]. A 2017 retrospective analysis of 120 participants enrolled in the DIVAS study, a parallel design based on a food-exchange model of SFA, monounsaturated (MUFA), and polyunsaturated fatty acid (PUFA) intakes in free-living individuals for 16 wk, reported that only APOE rs1064725-TT homozygotes, but not G allele carriers, showed a reduction in serum TC concentrations after the MUFA diet (−0.71 ± 1.88 mmol/L) compared to the SFA (0.34 ± 0.55 mmol/L) or n-6 PUFA diets (−0.08 ± 0.73 mmol/L) [23]. A German diabetes study evaluated the interaction between dietary patterns, using FFQ data, and APOE polymorphisms in 348 diabetic patients, where among carriers of the APOE ε2 isoform (E2/E2, E2/E3; rs429258: TT, rs7412: TT/CT), lower versus higher consumption frequencies of butter, cream cake, French fries, or alcoholic beverages were independently associated with a 40% reduction in serum LDL-C concentrations [24]. In a randomized crossover design involving 63 mildly hypercholesterolemic individuals who consumed 2 g/d of PS for 28 d, carriers of the APOE ε4 isoform had a greater reduction in serum LDL-C concentrations (−0.31 ± 0.07 mmol/L Nutrients 2021, 13, 695 9 of 15

vs. −0.13 ± 0.05 mmol/L) compared to carriers of the APOE ε3 isoform [25]. This study also reported an interaction between APOE and CYP7A1-rs3808607, where participants of all genosets, except for CYP7A1-rs3808607 T/T + APOE ε3, showed reductions in LDL-C concentrations in response to PS consumption [25]. Furthermore, in a secondary analysis of data from the RISCK study, a 24-wk five-arm parallel intervention involving 389 adults, carriers of E4 relative to E3/E3 showed greater decreases in plasma TC concentrations (−0.28 ± 0.13 mmol/L) when SFA was replaced with low glycemic index (GI) carbohydrate on a lower fat diet, and a relative increase in TC concentrations (0.30 ± 0.14 mmol/L) when SFA was replaced with MUFA and high GI carbohydrates [26].

3.3. Genes Encoding Additional Proteins Involved in the Cholesterol Metabolic Pathway Cholesteryl ester transfer protein (CETP) exchanges TG from lipoproteins (VLDL or LDL) with cholesteryl esters from HDL particles [54]. In the CORDIOPREV clinical trial involving 424 Spanish participants with metabolic syndrome (MetS) who received a Mediterranean diet rich in fat from olive oil (35% fat, 22% MUFA) or a low-fat diet (28% fat, 12% MUFA), carriers of the minor allele (T) at rs3764261 in CETP showed higher plasma HDL-C concentrations (1.06 ± 0.03 vs. 0.98 ± 0.02 mmol/L) compared to GG homozygotes after 1 y on the Mediterranean diet, but not after the low-fat diet [27]. The CETP rs3764261– diet interaction was more recently investigated among 4700 adults from the Tehran Lipid and Glucose Study, a population-based prospective design, where among carriers of the T (published as A) allele, serum TC concentrations decreased from 8.02 to 5.58 mmol/L as fish intake increased from <3.6 g/d (quartile 1) through >14.9 g/d (quartile 4) compared to GG (published as CC) homozygotes, after 3.6 years of follow-up [28]. Cholesterol 7-alpha hydroxylase, encoded by CYP7A1, is a rate-limiting in the classic bile acid synthesis pathway in the . CYP7A1 rs3808607 has been associated with inter-individual variability in circulating cholesterol concentrations in response to dietary intakes. For instance, after 4 wk on a crossover design with dairy versus dairy-free diets, we have previously shown that carriers of the rs3808607-G allele had higher serum TC concentrations (ranging between 0.20 ± 0.06 and 0.28 ± 0.12 mmol/L for GT and GG genotypes, respectively) compared to TT homozygotes (−0.11 ± 0.08 mmol/L) [15]. In re- sponse to PS intake, however, the rs3808607-GG homozygotes showed greater a reduction in serum LDL-C concentrations (−0.46 ± 0.12 vs. −0.05 ± 0.07 mmol/L) compared to the TT homozygotes [25]. In yet another crossover design involving 30 mildly hyperc- holesterolemic adults who received a breakfast that contained either 3 g of high molecular weight barley β-glucan or a control diet daily for 5 wk each, carriers of the rs3808607-G allele showed greater reduction in serum TC concentrations (−0.58 and −0.70 mmol/L for GT and GG genotypes, respectively) compared to TT homozygotes (−0.31 mmol/L) [29]. The 7-dehydrocholesterol reductase, encoded by DHCR7, is the enzyme that catalyzes the terminal reaction of cholesterol synthesis in the liver. In response to dairy intervention, carriers of the DHCR7 rs760241 minor allele (A) showed higher serum LDL-C concen- trations (0.26 ± 0.08 vs. 0.06 ± 0.05 mmol/L) relative to GG homozygotes [15]. To our knowledge, this study by members of our group was the first, and thus far only, evidence of such interaction between the DHCR7 SNP rs760241 and dietary intake. Lipoprotein lipase, encoded by LPL, is an enzyme catalyzing the hydrolysis of TG from apoB-containing lipoproteins. A 2014 dietary intervention involving 56 healthy young Chinese showed that only male carriers of the LPL rs326 minor allele (G) had an increase in plasma HDL-C concentrations (1.32 ± 0.27 vs. 1.21 ± 0.21 mmol/L) after versus before a 6-d diet of high-carbohydrate (70.1% energy)/low-fat (13.7% energy) [30]. In the cross-sectional Chennai Urban Rural Epidemiological Study, involving type 2 diabetes cases and controls from India, carriers of the LPL rs1121923 minor allele (T) exhibited higher serum HDL-C concentrations (1.2 vs. 1.1 mmol/L) compared to CC homozygotes after consumption of a higher fat diet (3rd tertile: 28.4 ± 2.5% energy), as assessed by a semi-quantitative FFQ [31]. No differences were observed among genotypic groups consuming a diet providing less than 23.5% of energy from fat. Nutrients 2021, 13, 695 10 of 15

Hepatic lipase, encoded by LIPC, is an enzyme involved in reverse cholesterol trans- port. In a 2017 crossover, randomized controlled trial involving 42 Caribbean Hispanics, carriers of the LIPC rs1800588 major allele (C) had higher plasma HDL-C concentrations (1.3 ± 0.03 vs. 1.1 ± 0.04 mmol/L during phase 1, and 1.4 ± 0.03 vs. 1.2 ± 0.03 mmol/L dur- ing phase 2 of the trial) after consuming a high-fat Western diet (39% energy) compared to a low-fat traditional Hispanic diet (20% energy) for 4 wk each, whereas no difference was ob- served between Western and Hispanic diets among TT homozygotes [32]. In the POUNDS LOST trial, a long-term weight-loss intervention with diets varying in macronutrient com- position, overweight and obese carriers of the LIPC rs2070895 minor allele (A) showed an increase in serum TC concentrations (β ± SE: 0.19 ± 0.07 mmol/L) on a high-fat diet (40% energy) and a slight decrease in HDL-C concentrations (β ± SE: −0.04 ± 0.02 mmol/L) on a low-fat diet (20% energy) compared to rs2070895-GG homozygotes at 2 yr of the intervention [33].

4. Combinatory Patterns of SNPs Influencing Changes in Blood Cholesterol Concentrations in Response to Dietary Interventions Recently, the availability of low-cost genetic testing kits and new bioinformatic tools has allowed significant progress in understanding the complex interplay between genetics and diet. Development of GRS, in which various SNPs information is aggregated, offers a valuable approach to explain a higher percentage of variability in blood cholesterol profiles compared to analyzing individual SNPs [10,11]. In a study published in 2015, Justesen et al. investigated the effect of the interac- tion between GRS and lifestyle factors, including diet, on fasting serum lipid concentra- tions in a population-based Danish cohort comprised of 5961 male and female partici- pants (mean age = 46.1 y, mean BMI = 26.3 kg/m2)[55]. GRS of increased TC (74 loci), LDL-C (58 loci), or triglyceride (TG) (39 loci), and decreased HDL-C (71 loci) concentrations were built based on SNPs previously identified following GWAS of circulating fasting lipid concentrations. Dietary habits were estimated following dietary questionnaires and were classified as unhealthy, moderately healthy, and healthy. There was no significant effect of GRS and dietary habit interaction on baseline fasting serum cholesterol concentrations. The effect of specific components of the diet was not investigated. In a secondary analysis of data from the Food4Me study, a multi-country European online randomized controlled intervention exploring the potential for personalized nu- trition to enhance nutritional and health outcomes, the authors built a GRS based on 14 SNPs previously identified in GWAS of components of MetS and that showed a signif- icant association with any component of MetS at baseline of the intervention [56]. Thus, most selected SNPs had no existing association with cholesterol metabolism and trans- port. They found that after 6 months of intervention, among the 1263 male and female participants (mean age = 40.8 y, mean BMI = 25.4 kg/m2), those with a low GRS exhibited a significantly higher decrease in TC concentrations, compared to those with a high GRS (approximately −0.1 mmol/L), independently of Mediterranean diet adherence level. In a secondary analysis of data from a randomized crossover study [15], members of our group demonstrated a combinatory action of three SNPs in cholesterol-related genes, where among 101 normocholesterolemic participants (age = 18–69 y), carriers of the geno- typic combination of ABCG5 rs6720173-C, CYP7A1 rs3808607-TT, and DHCR7 rs760241-GG exhibited a maximal reduction in serum LDL-C concentrations relative to a combina- tion of rs6720173-GG, rs3808607-G, and rs760241-A genotypes (change: −0.37 ± 0.12 vs. 0.38 ± 0.14 mmol/L), following a blended dairy (3 servings/d for 4 wk) versus dairy-free intervention [57]. In a 2019 study, Guevara-Cruz et al. investigated the effect of the interaction between a GRS and a dietary intervention on serum HDL-C concentrations in 67 Mexican adults (20–60 y) with a BMI ≥ 25 kg/m2 and who had at least three out of five positive criteria for MetS [58]. The dietary intervention consisted in the consumption for 2.5 months of a diet following the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) guidelines, i.e., low in saturated (<7% energy) and cholesterol Nutrients 2021, 13, 695 11 of 15

(<200 mg/d), with 20–30 g/d fiber and a 25% reduction in total energy intake. The GRS consisted of six SNPs previously associated with MetS in GWAS, lifestyle intervention studies, and meta-analyses, and that were associated with changes in serum HDL-C concentrations following dietary intervention. The GRS built explained 42% of the variance in HDL-C concentrations following the NCEP-ATP III diet, and participants with a low GRS displayed an increase (0.08 mmol/L) in HDL-C concentrations, whereas participants with a high GRS had a decrease in HDL-C concentrations (−0.08 mmol/L). Additionally, these results were validated in an independent clinical cohort of 89 participants with MetS following a similar dietary intervention. Collectively, these studies show that the additive effect of several SNPs, which taken individually may have small independent effects, could explain a greater part of the vari- ability in response to a dietary intervention when combined. These data show the advantage of complex analyses including combinatory patterns of SNPs compared to the relatively low predictive value of individual SNP approaches. Although these models are promising for personalized dietary advice, the results are variable and require validation in controlled dietary interventions, including different age groups, gender, and across ethnicities.

5. Conclusions This review highlights the most recent findings from studies investigating the effects of SNP–diet interactions on blood cholesterol concentrations, where 20 SNPs in 14 cholesterol- related genes showed significant associations with various dietary intakes. This review also underscores important progress in the field, given the emerging scientific literature on the effect of combinations of SNPs on blood cholesterol concentrations in interaction with dietary intakes. This approach is likely to increase the explained variability in such a complex phenotype, and offers a valuable insight into the relationship between diet and CVD risk. Dietary interventions designed to lower circulating cholesterol concentrations, such as those limiting intakes of trans fat from processed foods, or replacing saturated fatty acids with unsaturated fatty acids, for example, are established means for reducing the risk of developing CVD, regardless of a person’s genetic makeup. Carriers of certain genotypes within cholesterol-related genes may, however, respond far better than others to a given dietary intervention, possibly leading to an improved cardiovascular health outcome. For instance, a reduction of approximately 10% in LDL-C concentrations was observed in adults carrying the genotypic combination of ABCG5 rs6720173-C, CYP7A1 rs3808607- TT, and DHCR7 rs760241-GG, relative to the combination of rs6720173-GG, rs3808607- G, and rs760241-A genotypes, after dairy versus dairy-free diets [57]. With evidence suggesting at least 1% reduction in CVD incidence or mortality with each 1% reduction in LDL-C or TC concentrations [12,59,60], the clinical impact of such nutrigenetic studies is obvious. Still, in addition to factors such as dietary components and population groups, it is imperative that the type of genetic mutation, whether missense, , or other, is also considered when assessing the potential impacts on the gene products. Of the individual SNPs reported in this review, six variants are listed by the Single Nucleotide Polymorphism Database (dbSNP) as missense variants (ABCA1 rs9282541 and rs2230806, ABCG5 rs6720173, ABCG8 rs6544718, APOE rs7412, and DHCR7 rs760241), thus describing changes in single nucleotides that result in different amino acid sequences, while others include intron, upstream transcript, synonymous, 5 prime UTR, or 3 prime UTR variants. Considering the type of genetic mutation may provide some mechanistic insight into the interpretation and discussion of findings in association studies, especially when detailed reports on the molecular mechanisms of action in the field are rarely available. Future research, including multi-site intervention trials, should take such clinical and mechanistic aspects into consideration and, furthermore, explore combinatory patterns of genetic variability in order to better understand the impact of gene–diet interactions on serum lipid profiles, and the potential cardiovascular impacts thereof. The individual SNPs Nutrients 2021, 13, 695 12 of 15

reported in this review, and those previously reported [8], are good starting candidates to build GRS aiming at predicting changes in blood cholesterol concentrations in response to dietary interventions. As an additional tool to advance the field, the availability of artificial intelligence and machine-learning approaches for identifying panels of SNPs, which in combination could better predict an individual’s lipid response to dietary interventions, offer tremendous potential [61]. The latter methods may allow a more rapid advancement of the field of personalized nutrition.

Author Contributions: Conceptualization, M.M.H.A., I.V.-V., D.J.B., P.J.H.J. and C.D.; methodology and formal analysis, M.M.H.A., I.V.-V., D.J.B., P.J.H.J. and C.D.; writing—original draft preparation, I.V.-V., M.M.H.A., and C.D.; writing—review and editing, M.M.H.A., I.V.-V., D.J.B., J.D.H., P.J.H.J. and C.D.; Project administration and funding acquisition, P.J.H.J. and J.D.H. All authors have read and agreed to the published version of the manuscript. Funding: I.V.-V. received research funding from the International Life Sciences Institute North America (Grant 320188). Supported by the Dietary Lipids Committee, North American Branch of the International Life Sciences Institute (ILSI North America). ILSI North America is a public, nonprofit scientific foundation that provides a forum to advance understanding of scientific issues related to the nutritional quality and safety of the food supply by sponsoring research programs, educational seminars and workshops, and publications. ILSI North America receives support primarily from its industry membership. ILSI NA was not involved in the review process and provided no comments on the interpretation of the findings. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: Disclosure I.V.-V. received stipend support from the grant received from ILSI NA. No other conflicts of interest are declared. M.M.H.A. declares no conflict of interest. D.J.B. is the Government liaison to the International Life Sciences Institute, North America Committee on Dietary Lipids. He receives no compensation in that role. J.D.H. serves as Co-Chair of the Canadian Leadership Team for ILSI NA, and currently serves as administrative lead for the research grant received from ILSI NA in support of this review. P.J.H.J. has received research grants from Nutritional Fundamentals for Health Inc., Mitacs, and the International Life Science Institute. He also owns stock in Nutritional Fundamentals for Health Inc. C.D. declares no conflict of interest.

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